viously applied in the Alps of Europe. Adjustment coefficients have been derived for 28 rainfall periods using 59 independent gauges of a quality-checked training data set. The validation was based on an independent data set composed of gauges located in eleven 20 ? 20 km2 validation areas, which are representative of different climate, topography and radar distance conditions. The WR and WMR methods were found preferable with a slight better performance of the latter. Furthermore, a novel approach has been adopted in this study, whereby radar estimates are considered useable if they provide information that is better than gauge-only estimates. The latter was derived by spatial interpolation of the gauges belonging to the training data set. Note that these gauges are outside the validation areas. As for the radar-adjusted estimates, gauge-derived estimates were assessed against gauge data in the validation areas. It was found that radar-based estimates are better for the validation areas at the dry climate regime. At distances larger than 100 km, the radar underestimation becomes too large in the two northern validation areas, while in the southern one radar data are still better than gauge interpolation. It is concluded that in ungauged areas of Israel it is preferable to use WMR-adjusted (or alternatively, simply WR-adjusted) radar echoes rather than the standard bulk adjustment method and for dry ungauged areas it is preferable over the conventional gauge-interpolated values derived from point measurements, which are outside the areas themselves. The WR and WMR adjustment methods provide useful rain depth estimates for rainfall periods for the examined areas but within the limitation stated above.
Analysis of extreme hydrometeorological events is important for characterizing and better understanding the meteorological conditions that can generate severe rainstorms and the consequent catastrophic flooding. According to several studies (e.g., Alpert et al., 2004; Wittenberg et al., 2007), the occurrence of such extreme events is increasing over the eastern Mediterranean although total rain amounts are generally decreasing. The current study presents an analysis of an extreme event utilizing different methodologies: (a) synoptic maps and high resolution satellite imagery for atmospheric condition analysis; (b) rainfall analysis by rain gauges data; (c) meteorological radar rainfall calibration and analysis; (d) field measurements for estimating maximum peak discharges; and, (e) high resolution aerial photographs together with field surveying for quantifying the geomorphic impacts. The unusual storm occurred over Israel between 30 March and 2 April, 2006. Heavy rainfall produced more than 100mm in some locations in only few hours and more than 200mm in the major core area. Extreme rain intensities with recurrence intervals of more than 100 years were found for durations of 1 h and more as well as for the daily rain depth values. In the most severely affected area,Wadi Ara, extreme flash floods caused damages and casualties. Specific peak discharges were as high as 10–30m3/s/km2 for catchments of the size of 1–10 km2, values larger than any recorded floods in similar climatic regions in Israel.
Weather radar data contain detailed information about the spatial structures of rain fields previously unavail- able from conventional rain gauge networks. This information is of major importance for enhancing our understanding of precipitation and hydrometeorological systems. This study focuses on spatial features of convective rain cells in southern Israel where the climate ranges fromMediterranean to hyper-arid. Extensive data bases from two study areas covered by radar systems were analyzed. Rain cell features were extracted such as center location, area, maximal rain intensity, spatial integral of rain intensity, major radius length, minor radius length, ellipticity, and orientation. Rain cells in the two study areas were compared in terms of feature distributions and the functional relationships between cell area and cell magnitude, represented by maximal rain intensity and spatial integral of rain intensity. Analytical distribution functions were fitted to the empirical distributions and the log-normal function was found to fit well the distributions of cell area, maximal rain intensity and major and minor radius lengths. The normal distribution fits well ellipticity em- pirical distribution, and orientation distribution was well-represented by the normal or uniform distribution functions. The effect of distance fromtheMediterranean coastline on cell features was assessed. Amaximum of cell rain intensity at the coastline and maximum cell density 15 km inland from the coastline were found. In addition, a gradual change of cell orientation was observed with a northwest-southeast orientation 30 km from the coastline at the Mediterranean Sea and to almost a west-east orientation 30 km from the coastline inland
Weather radar systems provide detailed information on spatial rainfall patterns known to play a significant role in runoff generation processes. In the current study, we present an innovative approach to exploit spatial rainfall information of air mass thunderstorms and link it with a watershed hydrological model. Observed radar data are decomposed into sets of rain cells conceptualized as circular Gaussian elements and the associated rain cell parameters, namely, location, maximal intensity and decay factor, are input into a hydrological model. Rain cells were retrieved from radar data for several thunderstorms over southern Arizona. Spatial characteristics of the resulting rain fields were evaluated using data from a dense rain gauge network. For an extreme case study in a semi-arid watershed, rain cells were derived and fed as input into a hydrological model to compute runoff response. A major factor in this event was found to be a single intense rain cell (out of the five cells decomposed from the storm). The path of this cell near watershed tributaries and toward the outlet enhanced generation of high flow. Furthermore, sensitivity analysis to cell characteristics indicated that peak discharge could be a factor of two higher if the cell was initiated just a few kilometers aside.
A spatial rainfall model was applied to radar data of air mass thunderstorms to yield a rainstorm representation as a set of convective rain cells. The modeled rainfall was used as input into hydrological model, instead of the standard radar-grid data. This approach allows a comprehensive linkage between runoff responses and rainfall structures
Radar-based estimates of rainfall rates and accumulations are one of the principal tools used by the National Weather Service (NWS) to identify areas of extreme precipitation that could lead to flooding. Radar-based rainfall estimates have been compared to gauge observations for 13 convective storm events over a densely instrumented, experimental watershed to derive an accurate reflectivity–rainfall rate (i.e., Z–R) relationship for these events. The resultant Z–R relationship, which is much different than the NWS operational Z–R, has been examined for a separate, independent event that occurred over a different location. For all events studied, the NWS operational Z–R significantly overestimates rainfall compared to gauge measurements. The gauge data from the experimental network, the NWS operational rain estimates, and the improved estimates resulting from this study have been input into a hydrologic model to “predict” watershed runoff for an intense event. Rainfall data from the gauges and from the derived Z–R relation produce predictions in relatively good agreement with observed streamflows. The NWS Z–R estimates lead to predicted peak discharge rates that are more than twice as large as the observed discharges. These results were consistent over a relatively wide range of subwatershed areas (4–148 km2). The experimentally derived Z–R relationship may provide more accurate radar estimates for convective storms over the southwest United States than does the operational convective Z–R used by the NWS. These initial results suggest that the generic NWS Z–R relation, used nationally for convective storms, might be substantially improved for regional application.
Intense rainstorms cause debris flows on escarpments in hyperarid environments. In contrast with more temperate environments, there have been no direct observations on rainfall intensities and durations required for initiating debris flows in hyperarid environments. Here, we report rainfall volume and intensities, acquired by gauge and radar measurements, for two successive storms along the hyperarid (\textless50 mm/yr) western escarpment of the Dead Sea basin. These rainfall data were analyzed in conjunction with detailed mapping of debris flows that occurred during these storms to determine values of rainfall intensity and duration required to generate debris flows on the Dead Sea western escarpment. The first of the two analyzed storms occurred on 2 November 1995. During this storm, two convective cells rained sequentially within a 5 It period at the lower reaches of the Nahal David and the Nahal 'Arugot that dissects the western escarpment of the Dead Sea, Israel. This storm triggered debris flows in 38 small (\textless3 km(2)) and high-gradient drainage basins along the escarpment. Total rainfall volume and spatial distribution were determined by 10 cumulative rain gauges that were also used to calibrate rainfall-intensity distributions from radar data. For this storm, region, and landscape, rainfall intensities exceeding 30 mm/h for a duration of I h were required to initiate debris flows. A second storm in the same area on 1718 October 1997 allowed the evaluation of the results determined from the 1995 storm. In this second, more regional storm, maximum rainfall intensities were 19-27 mm/h for a duration of 45 min. These values, lower than the 30 mm/h minimal threshold defined in the previous storm, are consistent with the occurrence of only three debris flows. The small number of debris flows resulted from the concentration of the highest intensities of rainfall on the desert plateau and not directly on top of the canyon walls. Most first- to third-order basins draining the Dead Sea escarpment contain evidence of zero to three late Holocene (\textless3000 yr) debris flows. From analysis of the two storms, we propose that most of these debris flows were triggered by storms similar to the 2 November 1995 event in which localized convective cells had rainfall intensities of \textgreater30 mm/h and durations of at least 1 h. The small number of debris flows that has occurred during the late Holocene indicates that such events are rare at the scale of individual drainage basins.
Global precipitation is monitored from a variety of platforms including spaceborne, ground-, and ocean-based platforms. Intercomparisons of these observations are crucial to validating the measurements and providing confidence for each measurement technique. Probability distribution functions of rain rates are used to compare satellite and ground-based radar observations. A preferred adjustment technique for improving rain rate distribution estimates is identified using measurements from ground-based radar and rain gauges within the coverage area of the radar. The underwater measurement of rainfall shows similarities to radar measurements, but with intermediate spatial resolution and high temporal resolution. Reconciling these different measurement techniques provides understanding and confidence for all of the methods.
Meteorological radar is a remote sensing system that provides rainfall estimations at high spatial and temporal resolutions. The radar-based rainfall intensities (R) are calculated from the observed radar reflectivities (Z). Often, rain gauge rainfall observations are used in combination with the radar data to find the optimal parameters in the Z–R transformation equation. The scale dependency of the power-law Z–R parameters when estimated from radar reflectivity and rain gauge intensity data is explored herein. The multiplicative (a) and exponent (b) parameters are said to be “scale dependent” if applying the observed and calculated rainfall intensities to objective function at different scale results in different “optimal” parameters. Radar and gauge data were analyzed from convective storms over a midsize, semiarid, and well-equipped watershed. Using the root-mean-square difference (rmsd) objective function, a significant scale dependency was observed. Increased time- and space scales resulted in a considerable increase of the a parameter and decrease of the b parameter. Two sources of uncertainties related to scale dependency were examined: 1) observational uncertainties, which were studied both experimentally and with simplified models that allow representation of observation errors; and 2) model uncertainties. It was found that observational errors are mainly (but not only) associated with positive bias of the b parameter that is reduced with integration, at least for small scales. Model errors also result in scale dependency, but the trend is less systematic, as in the case of observational errors. It is concluded that identification of optimal scale for Z–R relationship determination requires further knowledge of reflectivity and rain-intensity error structure.
A new characteristic timescale of a catchment is presented, the response timescale (RTS). It is a range of averaging time intervals which, when applied to catchment rainfall, yield smoothed time series that best approximate that of the resultant runoff. In determining the RTS, nothing is assumed about the nature of the rainfall-runoff transformation. In addition, this new measure is shown to be robust against measurement errors. An objective, automatic, observations-based algorithm is described that introduces the concept of peaks density for the estimation of RTS. Estimation is exemplified for single and multiple rainfall-runoff events through application to small catchments in Panama and Israel. In all cases, relatively stable values of response timescale are obtained. It is concluded that at least for the case studies, the response timescale is an intrinsic characteristic of the catchment and it is generally expected to be different from the catchment lag time and time of concentration. INDEX
The transformation of rainfall into runoff at a basin outlet is the combined effect of many hydrological processes, which occur at a wide range of spatial and temporal scales. However, determining the scale of the combined hydrological response of the basin is still problematic and concepts for its definition are yet to be identified. In this paper high-resolution meteorological radar data are used for the determination of a characteristic temporal scale for the hydrological response of the basin - the 'response time scale' (Ts*). Ts* is defined as the time scale at which the pattern of the time-averaged radar rainfall hietograph is most similar to the pattern of the measured outlet runoff hydrograph. The existence of such similarity at a relatively stable time scale for a specific basin indicates that it is an intrinsic property of the basin and is related to its hydrological response. The identification of the response time scale is carried out by analysis of observations only, without assuming a specific rainfall-runoff model. Ts* is examined in four small basins (10-100 km2) in Israel. The spatial scale is assumed as the entire basin. For all analyzed basins a stable response time scale is identified. Relatively short time scales are found for the urban and arid basins (15-30 min), while for the rural basins longer time scale are identified (90-180 min). The issues of relationship between the response time scale and basin properties and modeling at the response time scale have yet to be determined. ?? 2001 Elsevier Science B.V. All rights reserved.
At times, a pronounced trough of low barometric pressure extends from equatorial Africa northward, over the Red Sea and the eastern Mediterranean countries, i.e., the Red Sea Trough. The associated weather is usually hot and dry, and consequently the atmosphere becomes conditionally unstable. In cases in which additional moisture is supplied and dynamic conditions become supportive, as the case analyzed here, intense thunderstorms occur, with extreme rain rates, hail and floods. The storm herein analyzed caused extensive damage both in casualties and property and evolved in two main consecutive phases: In the first a Mesoscale Convective System that moved from Sinai northward over Israel dominated, and in the second deep convection was organized mainly along a cold front. Data analysis indicates several synoptic-scale factors that had a supportive effect on the storm formation and intensification: Conditional instability established by the Red Sea trough, mid-level moisture transport from Northern Africa, and upper-level divergence imparted by both polar and subtropical jet streams over the Middle-East. Mesoscale features were further investigated by means of a hydro-meteorological observational analysis with high spatio-temporal resolution using raingauge and radar data, and satellite imagery. It is shown that local factors, particularly topographic effects, play a major role in the evolution, intensity and spatial organization of the convective activity. Our findings support results of a numerical study of another autumn rainstorm associated with the Red Sea trough. In the present case we identify an additional contributing factor, i.e., a mid-latitude upper-level trough that further intensified the storm as it was approaching the Middle-East.